火力与指挥控制2025，Vol.50Issue(3)：78-84,7.DOI:10.3969/j.issn.1002-0640.2025.03.011
基于遗传算法的改进无迹粒子滤波相对导航算法
An Improved Relative Navigation Algorithm of Unscented Particle Filter Based on Genetic Algorithm
邱琪涵 1丁晓 2孟秀云1
作者信息
- 1. 北京理工大学宇航学院,北京 100081
- 2. 上海机电工程研究所,上海 201109
- 折叠
摘要
Abstract
In order to solve the problem of measurement error in the relative navigation system of UAV formation flight,an improved unscented particle filter(UPF)information fusion algorithm for rela-tive navigation system is proposed.The relative motion model of UAV and the measurement model of inte-grated navigation system are established in this paper.To solve the problem of importance density func-tion selection in particle filter algorithm,unscented Kalman filter(UKF)is introduced into importance sampling.In the resampling stage of particle filter algorithm,an improved method based on genetic algo-rithm is proposed to improve particle diversity Finally,a mathematical simulation is carried out,and the results show that the proposed method can effectively estimate the relative motion information of UAVS,which is better than the unscented particle filter algorithm and particle filter algorithm.关键词
相对导航/粒子滤波/无迹卡尔曼滤波/遗传算法Key words
relative navigation/particle filter/unscented Kalman filter/genetic algorithm分类
航空航天引用本文复制引用
邱琪涵,丁晓,孟秀云..基于遗传算法的改进无迹粒子滤波相对导航算法[J].火力与指挥控制,2025,50(3):78-84,7.
